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September 10, 2026AIChE JournalOpen Access

Model predictive control with inline parameter adaptation for direct crystal growth rate regulation

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Authors

HYHuitian YuJZJiewen ZhaoHBHeiko Briesen

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Overview

Experimental study demonstrates direct crystal growth rate control in glycine crystallization, indicating improved stability and reduced retuning under dynamic process conditions.

Key Points

  • To develop and evaluate a growth kinetics-based model predictive control framework with inline parameter adaptation for real-time crystal growth rate regulation in batch cooling crystallization.
  • Implemented a kinetics-based model predictive control (MPC) scheme using an inline single-crystal growth rate sensor in a glycine batch cooling crystallization system.
  • Verified proxy crystal growth measurements through micro-computed tomography scans of sampled crystal populations.
  • Demonstrated stable closed-loop performance with real-time parameter adaptation, substantially decreasing the need for manual controller retuning across fluctuating operating conditions.
  • Revealed a physical limitation in constant-growth-rate control, showing that rising supersaturation during cooling induces secondary nucleation and strains cooling capacity.

Cite This Study

Yu et al. (2026) studied this question.

synapsesocial.com/papers/6aa27bbd58559d80afc75285https://doi.org/10.1002/aic.70648
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